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thesis](https://github.com/tangkk/phd-thesis-junqi-deng/blob/master/junqi-thesis-hku.pdf). The original [code](https://github.com/tangkk/tangkk-mirex-ace) of this work is written in matlab. So I try to port some of those code into python, but this is by no means a direct porting. This project is meant to be a minimalist version of ACE, which keeps only the algorithmic gist of the original work.\n\nCompared with the [original version](https://github.com/tangkk/tangkk-mirex-ace) which supports sevenths chords and inversions, this piece of code currently only supports maj and min triads, and it has much lighter (only a few lines of) feature extraction and segmentation codes.\n\n## What are the dependencies?\nIt depends on [librosa](https://github.com/librosa/librosa) for feature extraction and [hmmlearn](http://hmmlearn.readthedocs.io/en/stable/) for chord segmentation (as well as labeling if in the simple model)\n\nAlso install [keras](https://keras.io/) (and [theano](http://www.deeplearning.net/software/theano/) or [tensorflow](http://tensorflow.org/) also) to use the FCNN or RNN models, otherwise you could only run it in \"simple\" model.\n\n## How to install it?\n```\npip install pyace\n```\n\n## How to use it?\nFirst of all import the module by calling:\n```\nimport pyace\n```\n\nIt basically provides two simple interfaces:\n\n```\npyace.simpleace(songpath, respath)\n```\nand\n```\npyace.deepace(songpath, respath, modelpath, acemode)\n```\n## How to use it without installation?\nYou could just take the source code and run it as:\n```\npython pyace.py [songpath] [acemode] [modelpath]\n```\n\nThe acemode can be either 'simple', 'fcnn' or 'rnn'.\n\nFor example, try the following lines:\n```\npython pyace.py aizheni.mp3 simple\npython pyace.py aizheni.mp3 rnn ./model/lstmrnn512/CJKURB.cg.model\n```\nThe pretrained models as well as the testcases can be downloaded [here](https://www.dropbox.com/s/akyc2cxhdtgtm71/models.zip?dl=0)\n\n## Can I modify the code?\nThis is a very lite version of ACE. You are strongly encouraged to take this piece of code away and do whatever you want to.\n\n## How can I evaluate the results?\nPlease refer to the evaluation script provided (pyace/aceeval.py and eval.sh) for the evaluation process.\nThe process relies on the [MusOOEvaluator](https://github.com/jpauwels/MusOOEvaluator)\n\n## License\nThis software is under BSD License. For commercial use of this software, please contact the author.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftangkk%2Fpyace","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftangkk%2Fpyace","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftangkk%2Fpyace/lists"}